ChatGPT is more extroverted, conscientious, and more open to experiences than the average working age human, new research from Sapia.ai has found.
If these generative AI models were job candidates responding to interview questions, what kind of personality would they project in their natural form? ChatGPT (based on GPT-3.5) and more recently GPT-4 are built using a process that includes “reinforcement learning from human feedback (RLHF)” to produce responses which are less likely to make up facts, be toxic or harmful in their sentiment compared to the earlier GPT-2. Could this friendliness and politeness be verified through the personality these models project? These were some of the questions that the team at Sapia Labs, the innovation arm of Sapia.ai, set out to answer.
“We all know ChatGPT can be prompted to respond in different ways and, as AI models, personality is not directly applicable to them. However, given these models generate responses similar to humans, we wanted to better understand the personality projected by these models when they are not prompted to be a certain personality, or in its natural form, and be able to distinguish its responses from that of a human,” Sapia.ai’s Chief Data Scientist Dr. Buddhi Jayatilleke said.
The study, a first of its kind, analysed over 6,000 responses from GPT-2, ChatGPT (GPT-3.5) and GPT-4, and cross-examined them with Sapia.ai’s dataset (currently at 4 million candidates across 47 countries with over 1.5 billion words shared by job candidates). Sapia Labs used their industry-leading personality inference models based on InterviewBERT, a fine tuned version of Google’s BERT large language model to infer the personality dimensions similar to the well known HEXACO model of personality.
Their findings provide fascinating insights into the nature of these generative models. Both ChatGPT and GPT-4 scored significantly higher on the dimensions of honesty/humility, agreeableness, and consciousness compared to GPT-2. These results align well with OpenAI’s description of how ChatGPT models differ from earlier GPT models. The higher honesty/humility and agreeableness is consistent with modesty, politeness, and friendly responses. Additionally, the greater likelihood to follow directions and provide accurate information aligns with ChatGPT’s higher conscientiousness. But the most interesting finding is that both ChatGPT and GPT-4 showed significantly higher levels of extroversion, conscientiousness, and open to experience compared to the human benchmark dataset. In other words the newer GPT models trained with human-in-the-loop project a more sociable, open minded and diligent personality.
Global brands including Joe & the Juice, Starbucks, Woolworths Group, and Qantas trust Sapia.ai to accelerate and enhance their recruitment and promotion processes, bringing them the people who belong with their brands by giving every candidate a chance to interview over a low pressure chat.
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Mirrored diversity: why retail teams should look like their customers
Walk into any store this festive season and you’ll see it instantly. The lights, the displays, the products are all crafted to draw people in. Retailers spend millions on campaigns to bring customers through the door.
But the real moment of truth isn’t the emotional TV ad, or the shimmering window display. It’s the human standing behind the counter. That person is the brand.
The missing link in retail hiring
Most retailers know this, yet their hiring processes tell a different story. Candidates are often screened by rigid CV reviews or psychometric tests that force them into boxes. Neurodiverse candidates, career changers, and people from different cultural or educational backgrounds are often the ones who fall through the cracks.
And yet, these are the very people who may best understand your customers. If your store colleagues don’t reflect the diversity of the communities you serve, you create distance where there should be connection. You lose loyalty. You lose growth.
We call this gap the diversity mirror.
What mirrored diversity looks like
When retailers achieve mirrored diversity, their teams look like their customers:
- A grocery store team that reflects the cultural mix of its neighbourhood.
- A fashion store with colleagues who understand both style and accessibility.
- A beauty retailer whose teams reflect every skin tone, gender, and background that walks through the door.
Customers buy where they feel seen – making this a commercial imperative.
How to recruit seasonal employees with mirrored diversity
The challenge for HR leaders is that most hiring systems are biased by design. CVs privilege pedigree over potential. Multiple-choice tests reduce people to stereotypes. And rushed festive hiring campaigns only compound the problem.
That’s where Sapia.ai changes the equation: Every candidate is interviewed automatically, fairly, and in their own words.
- Bias is measured and monitored using Sapia.ai’s FAIR™ framework.
- Outcomes are validated at scale: 7+ million candidates, 52 countries, average candidate satisfaction 9.2/10.
- Diversity can be measured: with the Diversity Dashboard, you can track DEI capture rates, candidate engagement, and diversity hiring outcomes across every stage of the funnel.
With the right HR hiring tools, mirrored diversity becomes a data point you can track, prove, and deliver on. It’s no longer just a slogan.
Retail recruiting strategies in action: the David Jones example
David Jones, Australia’s premium department store, put this into practice:
- 40,000 festive applicants screened automatically
- 80% of final hires recommended by Sapia.ai
- Recruiters freed up 4,000 hours in screening time
- Candidate experience rated 9.1/10
The result? Store teams that belong with the brand and reflect the customers they serve.
Read the David Jones Case Study here 👇
Recruiting ideas for retail leaders this festive season
As you prepare for festive hiring in the UK and Europe, ask yourself:
- How much will you spend on marketing this Christmas?
- And how much will you invest in ensuring the colleagues who deliver that brand promise reflect the people you want in your stores?
Because when your colleagues mirror your customers, you achieve growth, and by design, you’ll achieve inclusion.
See how Sapia.ai can help you achieve mirrored diversity this festive season. Book a demo with our team here.
FAQs on retail recruitment and mirrored diversity
What is mirrored diversity in retail?
Mirrored diversity means that store teams reflect the diversity of their customer base, helping create stronger connections and loyalty.
Why is diversity important in seasonal retail hiring?
Seasonal employees often provide the first impression of a brand. Inclusive teams make customers feel seen, improving both experience and sales.
How can retailers improve their hiring strategies?
Adopting tools like AI structured interviews, bias monitoring, and data dashboards helps retailers hire fairly, reduce screening time, and build more diverse teams.
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The Diversity Dashboard: Proving your DEI strategy is working
Why measuring diversity matters
Organisations invest heavily in their employer brand, career sites, and EVP campaigns, especially to attract underrepresented talent. But without the right data, it’s impossible to know if that investment is paying off.
Representation often varies across functions, locations, and stages of the hiring process. Blind spots allow bias to creep in, meaning underrepresented groups may drop out long before offer.
Collecting demographic data is only step one. Turning it into insight you can act on is where real change and better hiring outcomes happen.
What is the Diversity Dashboard?
The Diversity Dashboard in Discover Insights, Sapia.ai’s analytics tool, gives you real-time visibility into representation, inclusion, and fairness at every stage of your talent funnel. It helps you connect the dots between your attraction strategies and actual hiring outcomes.
Key features include:
- Demographic filters – Switch between gender, ethnicity, English as an additional language, First Nations status, disability, and veteran status. View age and ethnicity in standard or alternative formats to match regional reporting needs.
- Representation highlights – Identify the top five represented sub-groups for each demographic, plus the three fastest-growing among underrepresented groups.
- Track trends over time – See month-by-month changes in representation over the past 12 months, compare to earlier periods, and connect the data back to your EVP and attraction spend.
- Candidate experience metrics – Measure CSAT (satisfaction) and engagement rates by demographic to ensure your hiring process works for everyone. Inclusion is measurable.
- Hiring fairness – Compare representation in your applied, recommended, and hired pools to spot drop-offs. Understand not just who applies, but who progresses — and why.
From insight to action
With the Diversity Dashboard, you can pinpoint where inclusion is thriving and where it’s falling short.
- See if your EASL candidates are applying in high numbers but not progressing to live interview.
- Spot if candidates with a disability report high satisfaction but have lower offer rates.
- Track the impact of targeted campaigns month-by-month and adjust quickly when something isn’t working.
It’s also a powerful tool to tell your success story. Celebrate wins by showing which underrepresented groups are making the biggest gains, and share that progress with boards, executives, and regulators.
Built on science, backed by trust
Powered by explainable AI and the world’s largest structured interview dataset, your insights are fair, auditable, and evidence-based.
Measuring diversity is the first step. Using that data to take action is where you close the Diversity Gap. With the Diversity Dashboard, you can prove your strategy is working and make the changes where it isn’t.
Book a demo to see the Diversity Dashboard in action.
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Neuroinclusion by design. Not by exception.
Why neuroinclusion can’t be a retrofit and how Sapia.ai is building a better experience for every candidate.
In the past, if you were neurodivergent and applying for a job, you were often asked to disclose your diagnosis to get a basic accommodation – extra time on a test, maybe the option to skip a task. That disclosure often came with risk: of judgment, of stigma, or just being seen as different.
This wasn’t inclusion. It was bureaucracy. And it made neurodiverse candidates carry the burden of fitting in.
We’ve come a long way, but we’re not there yet.
Shifting from retrofits to inclusive-by-design
Over the last two decades, hiring practices have slowly moved away from reactive accommodations toward proactive, human-centric design. Leading employers began experimenting with:
- Sharing interview questions in advance
- Replacing group exercises with structured simulations
- Offering a variety of assessment formats
- Co-designing assessments with neurodiverse candidates
But even these advances have often been limited in scope, applied to special hiring programs or specific roles. Neurodiverse talent still encounters systems built for neurotypical profiles, with limited flexibility and a heavy dose of social performance pressure.
Hiring needs to look different.
Insight 1: The next frontier of hiring equity is universal design
Truly inclusive hiring doesn’t rely on diagnosis or disclosure. It doesn’t just give a select few special treatment. It’s about removing friction for everyone, especially those who’ve historically been excluded.
That’s why Sapia.ai was built with universal design principles from day one.
Here’s what that looks like in practice:
- No time limits — Candidates answer at their own pace
- No pressure to perform — It’s a conversation, not a spotlight
- No video, no group tasks — Just structured, 1:1 chat-based interviews
- Built-in coaching — Everyone gets personalised feedback
It’s not a workaround. It’s a rework.
Insight 2: Not all “friendly” methods are inclusive
We tend to assume that social or “casual” interview formats make people comfortable. But for many neurodiverse individuals, icebreakers, group exercises, and informal chats are the problem, not the solution.
When we asked 6,000 neurodiverse candidates about their experience using Sapia.ai’s chat-based interview, they told us:
“It felt very 1:1 and trustworthy… I had time to fully think about my answers.”
“It was less anxiety-inducing than video interviews.”
“I like that all applicants get initial interviews which ensures an unbiased and fair way to weigh-up candidates.”
Insight 3: Prediction ≠ Inclusion
Some AI systems claim to infer skills or fit from resumes or behavioural data. But if the training data is biased or the experience itself is exclusionary, you’re just replicating the same inequity with more speed and scale.
Inclusion means seeing people for who they are, not who they resemble in your data set.
At Sapia.ai, every interaction is transparent, explainable, and scientifically validated. We use structured, fair assessments that work for all brains, not just neurotypical ones.
Where to from here?
Neurodiversity is rising in both awareness and representation. However, inclusion won’t scale unless the systems behind hiring change as well.
That’s why we built a platform that:
- Doesn’t rely on disclosure
- Removes ambiguity and pressure
- Creates space for everyone to shine
- Measures what matters, fairly
Sapia.ai is already powering inclusive, structured, and scalable hiring for global employers like BT Group, Costa Coffee and Concentrix. Want to see how your hiring process can be more inclusive for neurodivergent individuals? Let’s chat.